2) Mapping builds and reconstructs a consistent model to describe the surrounding environment. Mapping can be used to provide environment information for human operators and high-level robot tasks, constrain the error drifts of odometry estimation, and retrieve the inquiry observation for global localization [1]}.
Deep learning is leveraged as an useful tool to discover scene geometry and semantics from high-dimensional raw data for mapping. Deep learning based mapping methods are sub-divided into geometric, semantic, and general mapping, depending on whether the neural network learns the explicit geometry or semantics of a scene, or encodes the scene into an implicit neural representation respectively.
